The present invention generally relates to the field of image reconstruction in computed tomography (CT) systems and more particularly to a method and apparatus for reducing artifacts in image data caused by high density objects.
CT scanners operate by projecting fan shaped or cone shaped X-ray beams through an object. The X-ray beams are generated by an X-ray source, and are generally collimated prior to passing through the object being scanned. The attenuated beams are then detected by a set of detector elements. The detector elements produce a signal based on the intensity of the attenuated X-ray beams, and the signals are processed to produce projections. By using reconstruction techniques, such as filtered backprojection, useful images are formed from these projections.
A computer is able to process and reconstruct images of the portions of the object responsible for the radiation attenuation. As will be appreciated by those skilled in the art, these images are computed by processing a series of angularly displaced projection images. This data is then reconstructed to produce the reconstructed image, which is typically displayed on a cathode ray tube, and may be printed or reproduced on film.
One problem with reconstructed images in CT systems is artifacts caused by the presence of high density objects, for example, metal objects in a subject. The presence of such high density objects in a subject causes relatively high attenuation of the X-ray beams as they propagate through the subject, thereby resulting in a reconstructed image with artifacts. These artifacts can produce significant dark and bright streaks in the reconstructed image that severely limit the CT assessment of soft tissue and bone structures surrounding the high density objects. The artifacts are due to one or more effects such as beam hardening, poor signal-to-noise ratio, scattered radiation, partial volume effect, aliasing, and object motion.
Different solutions for metal artifacts reduction have previously been employed. For example, when a small metallic object is present in a scan, such as a metallic tooth filling or crown, adaptive filtration or interpolation methods are often applied on the sinogram domain of CT data, as the degrading effect of the metallic filling/crown is not very significant. For metallic objects significantly larger in size, such as a metal knee or prosthetic hip, the degrading effect increases and other reconstruction methods must be employed. One of these methods uses a polynomial model to address the increased beam hardening effect. Polynomial correction also has its limits however, as it works well only when the high density object in the patient is comprised of a homogenous material. As such, iterative algorithms are sometimes implemented, such as an EM (expectation maximization)-type algorithm or other iterative methods which incorporate beam hardening and other physical effects in the forward model.
A disadvantage of all the above techniques is that they result in either only a partial reduction of artifacts, introduce new artifacts, have a high computation time, or result in the formation of blurred images. Therefore, a need exists for a method of reducing or eliminating metal artifacts in CT imaging in a computationally-efficient, dose-efficient, and robust manner. Such a method would be able to accommodate high density objects of various sizes and compositions.